Adaptive User Interfaces

Papers from the AAAI Spring Symposium

As computers become more accessible, the problem of designing effective user interfaces becomes more severe. Many new users expect interacting with a computer to be as natural and intuitive as interacting with a person, but current interfaces are artificial and constraining. One particular weakness with most interfaces is their static nature. Programmers create these interfaces to interact identically with all users and for a range of tasks, without considering differences in knowledge, preferences, and purpose. At best, some interfaces allow limited customization by explicitly setting preferences and options.

A new cross-disciplinary approach has emerged in recent years from researchers in human-computer interaction, information extraction, machine learning, and other fields. In this approach, a system takes advantage of feedback from its user or the environment to adapt its performance. This adaptation can take a number of forms. Some examples include presenting different information to the user, altering the presentation order, changing the level of interaction, or describing information differently. Feedback is generally unobtrusive, with the goal of making the interface more effective without the burden of explicitly configuring the system. A popular approach is to model facets of the system's functionality with parameters, such as a user, task, or world model. An adaptive component estimates parameter values from feedback, and a performance component uses these values to control the information presented.